In this data point, frank notices a unique data collection

device while on holiday in Hilton Head, South Carolina.

Well, hello, LinkedIn, YouTube, Facebook, Twitch,

and Twitter or X or whatever it's called

this week. My name is Frank Lavinia. And I am

Juan. I'm on vacation in

Hilton Head, South Carolina. And one of the things

that happened was hurricane

ran through here. But fortunately, by the time IoT got to us, it was

pretty weak. We didn't lose power. There are a lot of down trees and stuff

like that, but one of the things

we were watching, the Weather Channel, apparently Florida got hit really bad, I think

big Bend, Florida. My thoughts and prayers

go out to them. It looks like it was pretty badly hit. Could have been

worse, I guess. But still, a category three hurricane is

nothing to play games with.

But the thing I wanted to talk about here, yes,

maybe it was a category four, you're right. My production assistant here,

who has been helping me test out the system,

I'll explain what I'm testing out in a

so actually, a couple of interesting

bikes just went by. One of the great things about

Hildehead Island, aside from IoT being on the sea and all that, is that there's

a number of bike trails through here, although the sign calls them

leisure trails because they're not strictly for bikes. People run on them, people

walk on them, people take their scooters on them,

et cetera, et cetera. So one of the things I noticed actually a couple of

days ago, and this proves that I'm always thinking about data, but I guess you

already knew that. Is there's

something here I saw in two different places, and I think it's interesting,

I've seen some variant of these along highways throughout my

life, but it's called Metro Count.

And from what I can tell,

it's bolted to the tree for one. Right. So I did a

quick actually, the URL is right down there, metrocount.com.

Not a commercial for Metrocount. I did a quick look

at their website. Apparently what they do is that they have these sensors in the

ground, and if you can see them, hopefully you

can see them. And

what this does let's see what the other end looks like.

These are two separate, according to the website, pneumatic

tubes that are placed about this far apart.

Sorry. And here goes a bike

now, kind of see, and for those of you listening to

this on the podcast, I will be sure to include links and stuff and

pictures. But

I've seen this in a couple of places here within this particular resort,

and I can only guess that they're trying to figure out

how much use people are getting on the bike trails. I don't know

why, but it is probably going to be an interesting data point. They have these

in I've seen at least two places here, these Metro Count

systems. And I looked at their

website briefly, and apparently they

can tell between pedestrians,

bikes and vehicles like cars.

Cars and bikes, I think are pretty easy to figure out. Pedestrians, I

suppose if one gets hit and the other one doesn't,

they might do that. Plus there's also the timing incident of it. And

there's actually a pretty lengthy section there.

The data analytics. The data, they do analytics or they provide

analytics and presumably an AI model of some sort.

They can tell you what type of vehicle it is. So

my junior engineer here

was running back and forth in this scooter hoping to see would we know,

right, that's what you were doing, you were trying to see if it registered the

scooter. So we don't have access to the data that it's

producing, but we can infer that it could

probably tell based on the timing and the

weight. It could definitely tell between bikes. It might even be able to tell between

kids bikes and adult bikes. Obviously, vehicles

are going to be much heavier and the timing of it, they can probably,

based on the distance infer the speed, the

distance apart. Although since it's not really fixed, you can,

I guess, mess with the wiring and kind of mess that up. I

don't know. But I just

find it interesting that they are collecting this type of data

on the island and I didn't get to shows you that data is everywhere.

Right? So just a fascinating look

kind of at the box, one last look at the box. And

if anyone within the sound of my voice works for Metro Count, I'll speak

for Andy here. Usually I don't like speaking for Andy, but I would love to

have you, I'm sure Andy would too love to have you on the show and

kind of talk about how this is used and how this works. Obviously nothing

proprietary, but I would imagine what this is doing is this is

let's call it what is, right? It's an edge device, right? And it's probably

I don't see an antenna, but that doesn't mean anything anymore.

And I left my radio wave detection thing

at home, which I wanted to

bring it, but the missus wasn't really into that.

These are the conversations that engineer families have.

But I think it's interesting. I'd love to know kind of like so

I'm assuming that these are some kind of robotic tubes based on what the website

described. And there's some kind of sensor in there, in here

that will register probably both timestamp and

the amount of pressure and weight, potentially. And I lost. There he

is. Probably that's how they do it. He's jumping over

it. So if you don't touch any of those, it doesn't register you.

So I guess a hoverboard, a proper hoverboard like from Back to the Future would

not register. Although if

the antigravity pad would do that. So these are the types of

we're going into nerd territory here. You're going to put a leaf on it. You

think a leaf will register? Probably not. I don't know. We'll find out.

Someone's going to be looking at this data and being like, what the heck?

There's a leaf on this. Assuming it's that sensitive.

What I'm assuming is happening here, I'm kind of reverse engineering this on the fly,

is that whatever weight gets pushed on there moves some

bit of air through the system. That device there

will register it, presumably to timestamp, too. There's probably

at least two, I would imagine, right? One for each one. And

I suppose one measures speed, and the

other one measures weight. And you have timing. You can kind of figure out

you can assume the weight. You can infer the weight and get

the weight, but you can infer the speed based on how that's going.

So I don't know. I just think it's interesting. It's kind of sad that I'm

on vacation, and I'm still thinking about data, but I

didn't choose data life. Data life chose me. So from

sunny Hilton Head Island. No,

no, it's good on the vacation. It's just kind of funny that I'm thinking about

data and stuff like that. But as I said, I didn't choose a data

life. The data life chose me. And the little one wants to

go back to the beach. I can't say IoT I blame him. So from Sunny

we're going to go back to the beach. I promise. This is like the Dunkin

Donuts episode all over again. All right, just

just 1 second. I'm going to close this out. So thanks for watching, and thanks

for listening, because I'm going to make this a data driven episode, too. But I

just think it's cool, and I just think it's interesting that I'm curious

how the community is going to use this data. Are they trying to justify the

maintenance, the upkeep on these things, and they're just trying to get

raw data on how this is used? How many people do it? I do wonder,

since E Scooters are technically not allowed, are they going to

use this to kind of figure out Escooters? I'm not saying

I know anyone in my family that has an E Scooter with us. I'm not

saying that. I'm just saying let's put it out there. I wonder if they're trying

to detect hoverboards and things like that with this system.

So with that, I'm going to end this

and signing off from Sunny Hill Head, South Carolina, and